Bioproduction of the aroma compound 2‐Phenylethanol in a solid–liquid two‐phase partitioning bioreactor system by <i>Kluyveromyces marxianus</i>
Bibliographic record
Abstract
The rose-like aroma compound 2-phenylethanol (2-PE) is an important fragrance and flavor ingredient. Several yeast strains are able to convert l-phenylalanine (l-phe) to 2-PE among which Kluyveromyces marxianus has shown promising results. The limitation of this process is the low product concentration and productivity primarily due to end product inhibition. This study explored the possibility and benefits of using a solid-liquid Two-Phase Partition Bioreactor (TPPB) system as an in situ product removal technique. The system applies polymer beads as the sequestering immiscible phase to partition 2-PE and reduce the aqueous 2-PE concentration to non-inhibitory levels. Among six polymers screened for extracting 2-PE, Hytrel 8206 performed best with a partition coefficient of 79. The desired product stored in the polymer was ultimately extracted using methanol. A 3 L working volume solid-liquid batch mode TPPB using 500 g Hytrel as the sequestering phase generated a final overall 2-PE concentration of 13.7 g/L, the highest reported in the current literature. This was based on a polymer phase concentration of 88.74 g/L and aqueous phase concentration of 1.2 g/L. Even better results were achieved via contact with more polymers (approximately 900 g) with the aqueous phase applying a semi-continuous reactor configuration. In this system, a final 2-PE concentration (overall) of 20.4 g/L was achieved with 1.4 g/L in the aqueous and 97 g/L in the polymer phase. The overall productivities of these two reactor systems were 0.38 and 0.43 g/L h, respectively. This is the first report in the literature of the use of a polymer sequestering phase to enhance the bioproduction of 2-PE, and exceeds the performance of two-liquid phase systems in terms of productivity as well as ease of operation (no emulsions) and ultimate product recovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".